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Pipeline run

2f90bb98-3906-41b7-baf3-fe2c3d12ef66

Pipeline LLM cost (USD)
API 1: $0.0041 API 2: $0.0000 API 3: $0.0000 Total: $0.0041

Client output enrichment

v2 Skill cluster · Nature of work · AI index · Tech stack maturity · Evidence · KRA description
Nature of work · AI/ML Engineering
Build and deploy generative-AI backend services in Python/.NET, prep and augment data, fine-tune models with chunks/embeddings, and integrate Azure/OpenAI or similar cloud services into scalable AI pipelines.
"• Design and develop backend services using Python or .NET to support OpenAI-powered solutions"
Tech stack maturity
Modern Cloud Native
The skill set centers on cloud platforms, containers, Kubernetes, and contemporary AI/ML tooling such as embeddings, OpenAI, PyTorch, and TensorFlow, which aligns with a modern cloud-native stack.
AI index (0 = no AI use, 5 = totally AI-dependent · v2.1)
3.20 / 5
Title match
Has AI skill
AI skill (primary)
· AI skill (secondary)
· On AI team
· Builds AI products
vocab breakdown (legacy)
Assistants (×1):
Frameworks (×2):
Models / concepts (×3): OpenAI, Transformers, embeddings, LLM, NLP, computer vision, multimodal, AI, GenAI, Generative AI, Machine Learning, Deep Learning
Evidence — skills matched in JD (24)
Python .NET OpenAI Azure Machine Learning Deep Learning Generative AI GANs VAEs Transformers Natural Language Processing TensorFlow PyTorch Keras GPT AWS GCP Docker Kubernetes Embeddings AI Pipelines Azure Cognitive Services Computer Vision Chunking
Skill cluster (8 dimension groups, role-scoped)
Cloud Platforms for AI Deployment
Azure AWS GCP
AI Governance and Model Security
Machine Learning
Containerization and Image Builds
Docker
Kubernetes for ML Workloads
Kubernetes
ML Frameworks and Libraries
Embeddings
Model Fine-Tuning & Adaptation
PyTorch
Python Programming
Python
Cross-cutting / unaligned
.NET OpenAI Deep Learning Generative AI GANs VAEs Transformers Natural Language Processing TensorFlow Keras GPT AI Pipelines Azure Cognitive Services Computer Vision Chunking
Show KRA description ↓
• Handle data preprocessing, augmentation, and generation of synthetic data. • Design and develop backend services using Python or .NET to support OpenAI-powered solutions (or any other LLM solution) • Develop and Maintaining AI Pipelines • Work with custom datasets, utilizing techniques like chunking and embeddings, to train and fine-tune models. • Integrate Azure cognitive services (or equivalent platform services) to extend functionality and improve AI solutions • Collaborate with cross-functional teams to ensure smooth deployment and integration of AI solutions. • Ensure the robustness, efficiency, and scalability of AI systems. • Stay updated with the latest advancements in AI and machine learning technologies. • Strong foundation in machine learning, deep learning, and computer science. • Expertise in generative AI models and techniques (e.g., GANs, VAEs, Transformers). • Experience with natural language processing (NLP) and computer vision is a plus. • Ability to work independently and as part of a team. • Knowledge of advanced programming like Python, and especially AI-centric libraries like TensorFlow, PyTorch, and Keras. This includes the ability to implement and manipulate complex algorithms fundamental to developing generative AI models. • Knowledge of Natural language processing (NLP) for text generation projects like text parsing, sentiment analysis, and the use of transformers like GPT (generative pre-trained transformer) models. • Experience in Data management, including data pre-processing, augmentation, and generation of synthetic data. This involves cleaning, labeling, and augmenting data to train and improve AI models. • Experience in developing and deploying AI models in production environments. • Knowledge of cloud services (AWS, Azure, GCP) and understanding of containerization technologies like Docker and orchestration tools like Kubernetes for deploying , managing and scaling AI solutions • Should be able to bring new ideas and innovative solutions to our clients.

Signals

Skill ml-engineer
0.38
Alias ai-engineer
1.00
KRA ai-engineer
0.38

Post-classification

Centroidupdated · n=22
Alias collision log
New-role queue
New skills captured13
New KRA capturedyes

Captured for admin review

.NET primary AI Engineer pending
Deep Learning primary AI Engineer pending
Generative AI primary AI Engineer pending
GANs primary AI Engineer pending
VAEs primary AI Engineer pending
Transformers primary AI Engineer pending
Natural Language Processing primary AI Engineer pending
Computer Vision AI Engineer pending
Keras primary AI Engineer pending
GPT primary AI Engineer pending
Chunking AI Engineer pending
AI Pipelines primary AI Engineer pending
Azure Cognitive Services primary AI Engineer pending
R&R fragment (sim 0.38) AI Engineer pending

• Handle data preprocessing, augmentation, and generation of synthetic data. • Design and develop backend services using Python or .NET to support OpenAI-powered solutions (or any other LLM solution) …

Status: extract_from_jd_done Created: 2026-05-19T23:08:16.916371Z Updated: 2026-05-19T23:08:18.196853Z
Flow Current 3-step pipeline

1 POST /skills/extract-from-jd

2 POST /skills/extract-details

3 POST /skills/final-role-output

Role Chosen role & resolution

No chosen role stored for this run.

Job description

Gen AI Engineer - Coimbatore

Role –Senior Gen AI Engineer

Experience : 3 Yr To 12 Yr

Location : Coimbatore

Mode of Interview - In Person

Date : 11th Oct 2025 (Saturday)

Job Description

• Collect and prepare data for training and evaluating multimodal foundation models. This may involve cleaning and processing text data or creating synthetic data.
• Develop and optimize large-scale language models like GANs (Generative Adversarial Networks) and VAEs (Variational Autoencoders)
• Work on tasks involving language modeling, text generation, understanding, and contextual comprehension.
• Regularly review and fine-tune Large Language models to ensure maximum accuracy and relevance for custom datasets.
• Build and deploy AI applications on cloud platforms – any hyperscaler Azure, GCP or AWS.
• Integrate AI models with our company's data to enhance and augment existing applications.


Role & Responsibility

• Handle data preprocessing, augmentation, and generation of synthetic data.
• Design and develop backend services using Python or .NET to support OpenAI-powered solutions (or any other LLM solution)
• Develop and Maintaining AI Pipelines
• Work with custom datasets, utilizing techniques like chunking and embeddings, to train and fine-tune models.
• Integrate Azure cognitive services (or equivalent platform services) to extend functionality and improve AI solutions
• Collaborate with cross-functional teams to ensure smooth deployment and integration of AI solutions.
• Ensure the robustness, efficiency, and scalability of AI systems.
• Stay updated with the latest advancements in AI and machine learning technologies.


Skills & Experience

• Strong foundation in machine learning, deep learning, and computer science.
• Expertise in generative AI models and techniques (e.g., GANs, VAEs, Transformers).
• Experience with natural language processing (NLP) and computer vision is a plus.
• Ability to work independently and as part of a team.
• Knowledge of advanced programming like Python, and especially AI-centric libraries like TensorFlow, PyTorch, and Keras. This includes the ability to implement and manipulate complex algorithms fundamental to developing generative AI models.
• Knowledge of Natural language processing (NLP) for text generation projects like text parsing, sentiment analysis, and the use of transformers like GPT (generative pre-trained transformer) models.
• Experience in Data management, including data pre-processing, augmentation, and generation of synthetic data. This involves cleaning, labeling, and augmenting data to train and improve AI models.
• Experience in developing and deploying AI models in production environments.
• Knowledge of cloud services (AWS, Azure, GCP) and understanding of containerization technologies like Docker and orchestration tools like Kubernetes for deploying , managing and scaling AI solutions
• Should be able to bring new ideas and innovative solutions to our clients

Skills from this JD

Each row merges API 1 extraction, API 2 library match / v3 orchestration (dimensions + locked dims), and API 3 persistence tags.

Python Primary No API 2 row (run stopped after API 1 or history missing)
.NET Primary No API 2 row (run stopped after API 1 or history missing)
OpenAI Primary No API 2 row (run stopped after API 1 or history missing)
Azure Primary No API 2 row (run stopped after API 1 or history missing)
Machine Learning Primary No API 2 row (run stopped after API 1 or history missing)
Deep Learning Primary No API 2 row (run stopped after API 1 or history missing)
Generative AI Primary No API 2 row (run stopped after API 1 or history missing)
GANs Primary No API 2 row (run stopped after API 1 or history missing)
VAEs Primary No API 2 row (run stopped after API 1 or history missing)
Transformers Primary No API 2 row (run stopped after API 1 or history missing)
Natural Language Processing Primary No API 2 row (run stopped after API 1 or history missing)
Computer Vision Secondary No API 2 row (run stopped after API 1 or history missing)
TensorFlow Primary No API 2 row (run stopped after API 1 or history missing)
PyTorch Primary No API 2 row (run stopped after API 1 or history missing)
Keras Primary No API 2 row (run stopped after API 1 or history missing)
GPT Primary No API 2 row (run stopped after API 1 or history missing)
AWS Primary No API 2 row (run stopped after API 1 or history missing)
GCP Primary No API 2 row (run stopped after API 1 or history missing)
Docker Primary No API 2 row (run stopped after API 1 or history missing)
Kubernetes Primary No API 2 row (run stopped after API 1 or history missing)
Embeddings Primary No API 2 row (run stopped after API 1 or history missing)
Chunking Secondary No API 2 row (run stopped after API 1 or history missing)
AI Pipelines Primary No API 2 row (run stopped after API 1 or history missing)
Azure Cognitive Services Primary No API 2 row (run stopped after API 1 or history missing)

Library artifacts (this run)

No artifact rows for this run.
nano JD Parser — gpt-4.1-nano click to toggle
RoleSenior Gen AI Engineer
Experience3 Yr To 12 Yr
DomainIT Services & Consulting
Location Coimbatore, India (null)
JD type pass
Show raw JSON
{
  "JD_type": "pass",
  "about_company": null,
  "certifications": [],
  "company_name": null,
  "ctc": null,
  "domain": {
    "primary": {
      "aliases": [],
      "domain": "IT Services \u0026 Consulting"
    },
    "secondary": null
  },
  "education": [],
  "experience": {
    "max": 12,
    "min": 3,
    "raw": "3 Yr To 12 Yr"
  },
  "job_locations": [
    {
      "aliases": [
        "Kovai"
      ],
      "city": "Coimbatore",
      "country": "India",
      "state": null,
      "work_mode": "null"
    }
  ],
  "role": "Senior Gen AI Engineer",
  "role_aliases": [
    "Gen AI Engineer",
    "Generative AI Engineer",
    "AI Engineer"
  ],
  "role_archetype": "Engineering",
  "roles_and_responsibilities": [
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      "bullet_count": 8,
      "heading": "Role \u0026 Responsibility",
      "heading_was_present": true,
      "source_marker": {
        "first_5_words": "\u2022 Handle data preprocessing, augmentation,",
        "last_5_words": "and machine learning technologies."
      },
      "text": "\u2022 Handle data preprocessing, augmentation, and generation of synthetic data.\n\u2022 Design and develop backend services using Python or .NET to support OpenAI-powered solutions (or any other LLM solution)\n\u2022 Develop and Maintaining AI Pipelines\n\u2022 Work with custom datasets, utilizing techniques like chunking and embeddings, to train and fine-tune models.\n\u2022 Integrate Azure cognitive services (or equivalent platform services) to extend functionality and improve AI solutions\n\u2022 Collaborate with cross-functional teams to ensure smooth deployment and integration of AI solutions.\n\u2022 Ensure the robustness, efficiency, and scalability of AI systems.\n\u2022 Stay updated with the latest advancements in AI and machine learning technologies.",
      "word_count": 92
    },
    {
      "bullet_count": 10,
      "heading": "Skills \u0026 Experience",
      "heading_was_present": true,
      "source_marker": {
        "first_5_words": "\u2022 Strong foundation in machine learning,",
        "last_5_words": "and innovative solutions to our clients."
      },
      "text": "\u2022 Strong foundation in machine learning, deep learning, and computer science.\n\u2022 Expertise in generative AI models and techniques (e.g., GANs, VAEs, Transformers).\n\u2022 Experience with natural language processing (NLP) and computer vision is a plus.\n\u2022 Ability to work independently and as part of a team.\n\u2022 Knowledge of advanced programming like Python, and especially AI-centric libraries like TensorFlow, PyTorch, and Keras. This includes the ability to implement and manipulate complex algorithms fundamental to developing generative AI models.\n\u2022 Knowledge of Natural language processing (NLP) for text generation projects like text parsing, sentiment analysis, and the use of transformers like GPT (generative pre-trained transformer) models.\n\u2022 Experience in Data management, including data pre-processing, augmentation, and generation of synthetic data. This involves cleaning, labeling, and augmenting data to train and improve AI models.\n\u2022 Experience in developing and deploying AI models in production environments.\n\u2022 Knowledge of cloud services (AWS, Azure, GCP) and understanding of containerization technologies like Docker and orchestration tools like Kubernetes for deploying , managing and scaling AI solutions\n\u2022 Should be able to bring new ideas and innovative solutions to our clients.",
      "word_count": 206
    }
  ],
  "urls": []
}
API 1 — extract-from-jd click to toggle
{
  "final_skills": [
    {
      "is_primary": true,
      "skill_name": "Python"
    },
    {
      "is_primary": true,
      "skill_name": ".NET"
    },
    {
      "is_primary": true,
      "skill_name": "OpenAI"
    },
    {
      "is_primary": true,
      "skill_name": "Azure"
    },
    {
      "is_primary": true,
      "skill_name": "Machine Learning"
    },
    {
      "is_primary": true,
      "skill_name": "Deep Learning"
    },
    {
      "is_primary": true,
      "skill_name": "Generative AI"
    },
    {
      "is_primary": true,
      "skill_name": "GANs"
    },
    {
      "is_primary": true,
      "skill_name": "VAEs"
    },
    {
      "is_primary": true,
      "skill_name": "Transformers"
    },
    {
      "is_primary": true,
      "skill_name": "Natural Language Processing"
    },
    {
      "is_primary": false,
      "skill_name": "Computer Vision"
    },
    {
      "is_primary": true,
      "skill_name": "TensorFlow"
    },
    {
      "is_primary": true,
      "skill_name": "PyTorch"
    },
    {
      "is_primary": true,
      "skill_name": "Keras"
    },
    {
      "is_primary": true,
      "skill_name": "GPT"
    },
    {
      "is_primary": true,
      "skill_name": "AWS"
    },
    {
      "is_primary": true,
      "skill_name": "GCP"
    },
    {
      "is_primary": true,
      "skill_name": "Docker"
    },
    {
      "is_primary": true,
      "skill_name": "Kubernetes"
    },
    {
      "is_primary": true,
      "skill_name": "Embeddings"
    },
    {
      "is_primary": false,
      "skill_name": "Chunking"
    },
    {
      "is_primary": true,
      "skill_name": "AI Pipelines"
    },
    {
      "is_primary": true,
      "skill_name": "Azure Cognitive Services"
    }
  ],
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    "rationale": null,
    "role_aliases": [
      "Gen AI Engineer",
      "Generative AI Engineer",
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    ],
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  },
  "nano_parsed": {
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    },
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      }
    ],
    "role": "Senior Gen AI Engineer",
    "role_aliases": [
      "Gen AI Engineer",
      "Generative AI Engineer",
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    ],
    "role_archetype": "Engineering",
    "roles_and_responsibilities": [
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        "bullet_count": 8,
        "heading": "Role \u0026 Responsibility",
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        },
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        "word_count": 92
      },
      {
        "bullet_count": 10,
        "heading": "Skills \u0026 Experience",
        "heading_was_present": true,
        "source_marker": {
          "first_5_words": "\u2022 Strong foundation in machine learning,",
          "last_5_words": "and innovative solutions to our clients."
        },
        "text": "\u2022 Strong foundation in machine learning, deep learning, and computer science.\n\u2022 Expertise in generative AI models and techniques (e.g., GANs, VAEs, Transformers).\n\u2022 Experience with natural language processing (NLP) and computer vision is a plus.\n\u2022 Ability to work independently and as part of a team.\n\u2022 Knowledge of advanced programming like Python, and especially AI-centric libraries like TensorFlow, PyTorch, and Keras. This includes the ability to implement and manipulate complex algorithms fundamental to developing generative AI models.\n\u2022 Knowledge of Natural language processing (NLP) for text generation projects like text parsing, sentiment analysis, and the use of transformers like GPT (generative pre-trained transformer) models.\n\u2022 Experience in Data management, including data pre-processing, augmentation, and generation of synthetic data. This involves cleaning, labeling, and augmenting data to train and improve AI models.\n\u2022 Experience in developing and deploying AI models in production environments.\n\u2022 Knowledge of cloud services (AWS, Azure, GCP) and understanding of containerization technologies like Docker and orchestration tools like Kubernetes for deploying , managing and scaling AI solutions\n\u2022 Should be able to bring new ideas and innovative solutions to our clients.",
        "word_count": 206
      }
    ],
    "urls": []
  },
  "rejected": false,
  "rejection_reason": null,
  "run_id": "2f90bb98-3906-41b7-baf3-fe2c3d12ef66",
  "stage3_signals": {
    "alias_found": true,
    "alias_match_roles": [
      {
        "display_name": "AI Engineer",
        "matched_count": null,
        "role_id": 13,
        "score": 1.0,
        "slug": "ai-engineer",
        "total_count": null
      }
    ],
    "kra_match_roles": [
      {
        "display_name": "AI Engineer",
        "matched_count": null,
        "role_id": 13,
        "score": 0.3787,
        "slug": "ai-engineer",
        "total_count": null
      },
      {
        "display_name": "AI Compliance Officer",
        "matched_count": null,
        "role_id": 12,
        "score": 0.3608,
        "slug": "ai-compliance-officer",
        "total_count": null
      },
      {
        "display_name": "ML Engineer",
        "matched_count": null,
        "role_id": 3,
        "score": 0.3583,
        "slug": "ml-engineer",
        "total_count": null
      },
      {
        "display_name": "Data Engineer",
        "matched_count": null,
        "role_id": 2,
        "score": 0.3387,
        "slug": "data-engineer",
        "total_count": null
      },
      {
        "display_name": "DevOps Engineer",
        "matched_count": null,
        "role_id": 10,
        "score": 0.338,
        "slug": "devops-engineer",
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      }
    ],
    "skill_match_roles": [
      {
        "display_name": "ML Engineer",
        "matched_count": 9,
        "role_id": 3,
        "score": 0.375,
        "slug": "ml-engineer",
        "total_count": 24
      },
      {
        "display_name": "ML Ops Engineer",
        "matched_count": 9,
        "role_id": 16,
        "score": 0.375,
        "slug": "ml-ops-engineer",
        "total_count": 24
      },
      {
        "display_name": "Backend Engineer",
        "matched_count": 5,
        "role_id": 1,
        "score": 0.2083,
        "slug": "backend-engineer",
        "total_count": 24
      },
      {
        "display_name": "DevOps Engineer",
        "matched_count": 5,
        "role_id": 10,
        "score": 0.2083,
        "slug": "devops-engineer",
        "total_count": 24
      },
      {
        "display_name": "AI Engineer",
        "matched_count": 5,
        "role_id": 13,
        "score": 0.2083,
        "slug": "ai-engineer",
        "total_count": 24
      }
    ]
  },
  "stage4_decision": {
    "alias_collision_detected": false,
    "case": "A",
    "chosen_role": {
      "display_name": "AI Engineer",
      "matched_count": null,
      "role_id": 13,
      "score": 1.0,
      "slug": "ai-engineer",
      "total_count": null
    },
    "confidence": 0.8,
    "llm2_fired": false,
    "llm2_reasoning": null,
    "queued": false,
    "reasoning": "Stage 1 title \u0027AI Engineer\u0027 (embedding match, sim 0.78); KRA inconclusive"
  },
  "stage5_updates": {
    "centroid_n_after": 22,
    "centroid_updated": true,
    "collision_log_id": null,
    "new_kra_attached": {
      "best_kra_similarity": 0.3787,
      "queue_id": 45,
      "r_and_r_preview": "\u2022 Handle data preprocessing, augmentation, and generation of synthetic data.\n\u2022 Design and develop backend services using Python or .NET to support OpenAI-powered solutions (or any other LLM solution)\n",
      "role_display_name": "AI Engineer",
      "role_slug": "ai-engineer",
      "status": "pending"
    },
    "new_skills_attached": [
      {
        "is_primary": true,
        "queue_id": 1484,
        "role_display_name": "AI Engineer",
        "role_slug": "ai-engineer",
        "skill_name": ".NET",
        "status": "pending"
      },
      {
        "is_primary": true,
        "queue_id": 1485,
        "role_display_name": "AI Engineer",
        "role_slug": "ai-engineer",
        "skill_name": "Deep Learning",
        "status": "pending"
      },
      {
        "is_primary": true,
        "queue_id": 1486,
        "role_display_name": "AI Engineer",
        "role_slug": "ai-engineer",
        "skill_name": "Generative AI",
        "status": "pending"
      },
      {
        "is_primary": true,
        "queue_id": 1487,
        "role_display_name": "AI Engineer",
        "role_slug": "ai-engineer",
        "skill_name": "GANs",
        "status": "pending"
      },
      {
        "is_primary": true,
        "queue_id": 1488,
        "role_display_name": "AI Engineer",
        "role_slug": "ai-engineer",
        "skill_name": "VAEs",
        "status": "pending"
      },
      {
        "is_primary": true,
        "queue_id": 1489,
        "role_display_name": "AI Engineer",
        "role_slug": "ai-engineer",
        "skill_name": "Transformers",
        "status": "pending"
      },
      {
        "is_primary": true,
        "queue_id": 1490,
        "role_display_name": "AI Engineer",
        "role_slug": "ai-engineer",
        "skill_name": "Natural Language Processing",
        "status": "pending"
      },
      {
        "is_primary": false,
        "queue_id": 1491,
        "role_display_name": "AI Engineer",
        "role_slug": "ai-engineer",
        "skill_name": "Computer Vision",
        "status": "pending"
      },
      {
        "is_primary": true,
        "queue_id": 1492,
        "role_display_name": "AI Engineer",
        "role_slug": "ai-engineer",
        "skill_name": "Keras",
        "status": "pending"
      },
      {
        "is_primary": true,
        "queue_id": 1493,
        "role_display_name": "AI Engineer",
        "role_slug": "ai-engineer",
        "skill_name": "GPT",
        "status": "pending"
      },
      {
        "is_primary": false,
        "queue_id": 1494,
        "role_display_name": "AI Engineer",
        "role_slug": "ai-engineer",
        "skill_name": "Chunking",
        "status": "pending"
      },
      {
        "is_primary": true,
        "queue_id": 1495,
        "role_display_name": "AI Engineer",
        "role_slug": "ai-engineer",
        "skill_name": "AI Pipelines",
        "status": "pending"
      },
      {
        "is_primary": true,
        "queue_id": 1496,
        "role_display_name": "AI Engineer",
        "role_slug": "ai-engineer",
        "skill_name": "Azure Cognitive Services",
        "status": "pending"
      }
    ],
    "queue_entry_id": null,
    "v3_pipeline_triggered": false,
    "v3_role_slug": null,
    "v3_run_id": null
  }
}
API 2 — extract-details
{}
API 3 — final-role-output
{}

LLM Calls

Every model call made for this run, in pipeline order. Click a card to see the model's response.

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